Peripheral nerve signal collection and electrical stimulation have important clinical application value in the treatment of nerve-related diseases (such as nerve palsy, epilepsy, Parkinson’s syndrome and spinal cord injury). Traditional nerve electrodes are usually made of hard metals or metal oxides (modulus of elasticity about 100 GPa). There are great mechanical characteristics between them and soft and dynamic biological tissues (modulus of elasticity about 100 KPa). And the mismatch in geometric structure. These differences will not only reduce the quality of the signal, but may also cause irreversible damage to the nerve bundle. In addition, nerve tissue mainly conducts signals through ions, while traditional electrodes conduct signals through electrons. This will lead to electrochemical reactions at the interface between the electrode and nerve tissue, resulting in the production of harmful substances, changes in environmental pH, or local Heat will disrupt the microenvironmental balance of the neural interface, thereby endangering the health of the tissue.
Recently, Zhang Yingying’s research group from the Department of Chemistry of Tsinghua University realized the construction of a super stretchable spring-like ion nerve electrode based on the asymmetric self-assembly phenomenon of two-dimensional nanomaterials in the direct writing 3D Printing process. The printing ink used in this work is a viscous sodium alginate aqueous solution dispersed with graphene oxide flakes. The researchers observed that the two-dimensional material in the ink undergoes an asymmetric self-assembly process during the printing and molding process, so that the printed strips show a gradient microstructure change. This structure is similar to the microstructure in some natural biological tissues (such as pine cones, bean pods, wheat awns). Then, cross-linking prevents the material from dissolving again in water. Due to the unique gradient structure change in the material, it can spontaneously deform into a spring-like structure when placed in water. The obtained structure has excellent elasticity and excellent ion conductivity, and has good matching properties with soft, dynamic and ion-conducting biological tissues, so that it can be used as a high-efficiency super-stretchable ion-conducting nerve electrode. The work was published on PNAS (Proc Natl Acad Sci USA) with the title “Microribbons composed of directionally self-assembled nanoflakes as highly stretchable ionic neural electrodes”. The first author is Zhang Mingchao, a doctoral student at Tsinghua University.
1. Asymmetric self-assembly of two-dimensional materials in the 3D printing process
Figure 1. Asymmetric self-assembly of graphene oxide sheets during direct-write 3D printing. The graphene oxide sheet in the viscous sodium alginate matrix undergoes an asymmetric self-assembly process during the printing process (Figure 1). Due to the strong shearing force during the extrusion process, the graphene oxide flakes in the ink will be aligned along the axial direction. In addition, when extruding from the needle, the high-viscosity ink will experience significant extrusion expansion, and the radial shear flow will drive the graphene oxide sheets to be aligned in the radial direction (it can be observed from the cross-section of the extruded fiber Graphene oxide sheets are arranged along the radial direction, Figure 1Bii). Furthermore, the extruded fibers are deposited on the substrate, and the graphene oxide sheets in the part close to the substrate gradually lie flat due to the limitation of the substrate and are aligned parallel to the substrate (Planar alignment); while the graphene oxide sheets in the part far away from the substrate are due to In the process of gradual evaporation of water, the viscosity of the system further increases and it is difficult to reorientate, so that the initial homeotropic alignment is maintained, thereby forming a self-assembled structure with gradient orientation changes.
Figure 2. The gradient of the microstructure can be controlled by adjusting the rheology of the printing paste and the temperature of the printing substrate. The degree of change in the above-mentioned gradient orientation can be adjusted by adjusting the rheological properties of the printing ink or adjusting the temperature of the printing substrate (Figure 2). When the water content in the slurry is higher, the viscosity is lower, and vice versa, the viscosity is higher. When a low-viscosity slurry is used for printing, almost all the graphene oxide of the resulting structure is aligned parallel to the orientation of the substrate; when a high-viscosity slurry is used for printing, the high viscosity will limit the reorientation of the graphene oxide sheet. As a result, the graphene oxide in the obtained structure has an orientation structure with a vertical arrangement. In addition, changing the temperature of the printing substrate is a simple way to affect the viscosity. An increase in temperature will increase the evaporation rate of water in the ink, thereby accelerating the increase in viscosity and inhibiting the reorientation of graphene oxide sheets. Therefore, the substrate at a higher temperature When printing on top, more graphene oxide orientation structures arranged along the vertical plane will be obtained. The difference in the orientation structure of graphene oxide will make the band have different mechanical properties in the local space. 3. The formation and micro-mechanism of the ultra-stretchable spring-like ion conducting strips. Due to the gradient change of the graphene oxide orientation structure in the printed strips, when the strips are placed in water, the upper and lower parts of the strip will expand in different directions when exposed to water. , Will produce bending moment, which spontaneously form a spring-like structure. By adjusting the degree of gradient orientation change, the structural parameters of the resulting spring structure can be adjusted (Figure 3). Graphene oxide sheets aligned in parallel in the resulting spring structure constitute a typical nanofluidic channel. At the same time, the graphene oxide-sodium alginate material has a high density of negative charges, so the positive charges can be in the nanofluidic channel. Efficient conduction in the flow channel. Experiments show that the spring structure in a low-concentration electrolyte exhibits an ionic conductivity that is several orders of magnitude higher than that of the electrolyte. In addition, due to its highly elastic spring-like structure, the ion conductor can still exhibit stable ion conductivity under strains as high as 1000%.
Figure 3. Due to the gradient change of the orientation structure of graphene oxide, when the printed strip is placed in water, a bending moment will be generated and spontaneously form a super stretchable spring-like structure. 4. Application display of super stretchable ion nerve electrode
Figure 4. The spring-like ion conduction nerve electrode is used for nerve signal collection and nerve electrical stimulation, and its performance is compared with the traditional metal platinum electrode. In order to demonstrate the application of the obtained material in nerve electrodes, the spring-shaped ion electrode was connected to the sciatic nerve of the bullfrog, and nerve signal recording and nerve electrical stimulation were performed (Figure 4). Compared with traditional rigid metal nerve electrodes with electron conduction characteristics, the prepared super-stretchable ion conduction nerve electrodes have better compatibility with soft, dynamic, and ion-conducting biological tissues. It can be seen from the figure that compared with the Pt electrode, the neuroelectric signal collected by the ion nerve electrode has a higher signal-to-noise ratio, and it also avoids the harmful electrochemical reaction and irreversible mechanical damage that may be caused by the traditional metal electrode. . These results demonstrate the application value of the highly stretchable ion-conducting structure obtained by 3D printing in nerve electrodes. The collaborators involved in this work include Professor Liu Jing and doctoral student Guo Rui from Tsinghua University School of Medicine, Dr. Chen Ke from Beijing University of Aeronautics and Astronautics School of Chemistry, Dr. Niu Jiali from Peking University, and Professor Metin Sitti from Max Planck Institute of Intelligent Systems Research in Germany. Wait.
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